Differentiable Antithetic Sampling for Variance Reduction in Stochastic
Variational Inference

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Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference

5 October 2018

Noah D. Goodman

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Papers citing "Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference"

7 / 7 papers shown

Title
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives Pierre-Alexandre Mattei J. Frellsen 125 4 0 26 Jan 2022
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary VariablesInternational Conference on Machine Learning (ICML), 2021 Alek Dimitriev Mingyuan Zhou 100 12 0 28 May 2021
Partition Function Estimation: A Quantitative StudyInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 Durgesh Kumar Agrawal Yash Pote Kuldeep S. Meel 152 12 0 24 May 2021
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables Zhe Dong A. Mnih George Tucker DRL 190 36 0 18 Jun 2020
Note on the bias and variance of variational inference Chin-Wei Huang Aaron Courville 119 5 0 09 Jun 2019
Hierarchical Importance Weighted AutoencodersInternational Conference on Machine Learning (ICML), 2019 Chin-Wei Huang Kris Sankaran Eeshan Gunesh Dhekane Alexandre Lacoste Aaron Courville BDL 136 16 0 13 May 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 364 114 0 03 Apr 2019